Volatile Organic Compound-Based Diagnostic Systems And Methods

ABSTRACT

Provided are devices and methods to detect the presence of volatile organic compounds related to the presence of a disease state in a biological sample. The devices may include a detection moiety such as a polynucleoide in electronic communication with a semiconductor such as graphene or a carbon nanotube.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a divisional of now-allowed U.S. Pat. ApplicationNo. 15/501,338, filed Feb. 2, 2017, which is the National StageApplication of International Patent Application No. PCT/US2015/048343,filed Sep. 3, 2015, which claims the benefit of and priority to U.S.Pat. Application No. 62/046,466, “volatile Organic Compound-BasedDiagnostic Systems and Methods” (filed Sep. 5, 2014). The entireties ofall of the foregoing applications are incorporated by reference hereinfor any and all purposes.

SEQUENCE LISTING

[0001.1] The instant application contains a Sequence Listing which hasbeen submitted electronically in ASCII format and is hereby incorporatedby reference in its entirety. Said ASCII copy, created on Jun. 25, 2018,is named 10324_006185_14-7186_SL.txt and is 1,582 bytes in size.

TECHNICAL FIELD

The present disclosure relates to the field of detection of volatilecompounds related to biomolecules and disease states and to the field ofsolid-state detector devices.

BACKGROUND

Cancer is a well-known, lethal disease, and ovarian cancer is the mostlethal of the gynecological cancers and the fourth leading cause ofcancer death in women. When diagnosed early, ovarian cancer has afavorable cure rate; however, more than 80% of patients are diagnosed ata late stage when even aggressive treatment is unable to effect a cure.Any advance that can lead to more accurate detection of ovarian cancerin its early stages would have a great impact on overall survival.

Despite extensive investigation, however, there is at present nosufficiently accurate screening test for early detection of cancer,particularly in patients of average risk. Accordingly, there is a needin the art for methods of screening samples for cancer (ovarian cancerin particular) and other disease states.

SUMMARY

In meeting the disclosed challenges, in one aspect the presentdisclosure provides detection devices, the devices comprising asemiconductor and a detection moiety in electronic communication withone another, the detection moiety being configured to detect one or morevolatile organic compounds present in a biological sample; and a sensorchamber, the device being configured such that the detection moiety iscapable of fluid communication with the interior of the sensor chamber.

In another aspect, the present disclosure provides methods, comprising:exposing a device (e.g., according to the present disclosure) to anatmosphere above a biological sample from a patient, the atmospherecomprising one or more volatile organic compounds of the sample; anddetecting a signal, a change in signal, or both related to exposing thedevice to the atmosphere.

The present disclosure also provides methods, comprising: exposing adevice (e.g., according to the present disclosure) to an atmosphereabove a biological sample from a patient, the atmosphere comprising oneor more volatile organic compounds of the sample; and detecting asignal, a change in signal, or both related to exposing the device tothe atmosphere.

BRIEF DESCRIPTION OF THE DRAWINGS

The summary, as well as the following detailed description, is furtherunderstood when read in conjunction with the appended drawings. For thepurpose of illustrating the invention, there are shown in the drawingsexemplary embodiments of the invention; however, the invention is notlimited to the specific methods, compositions, and devices disclosed. Inaddition, the drawings are not necessarily drawn to scale. In thedrawings:

FIG. 1 . Results of working dog training for ovarian cancer detection;testing against pooled plasma samples. The sensitivity is very high forall three dogs used.

FIGS. 2A and 2B. The top three plots show differences in selectedregions in the Total Ion Chromatographs obtained from analyses ofSPME-collected volatile organic compounds (VOCs) from the three pools ofsamples (top: control; middle: benign growth; bottom: ovarian cancer).The bottom two plots show the mass spectrometry data for the twocompounds that show the strongest differences. One is identified asdimethylsulfone and the second is a substituted benzaldehyde.

FIG. 3 . Current vs. gate voltage for a typical array of 28 devices fromone of the sensor arrays, measured with source-drain voltage of 100 mV.

FIG. 4 . The flow through each mass flow controller during theexperiments. After a 30 minute settling period to build-up the headspacevapors, two minute pulses of vapor from the serum headspaces werealternated with two minute chamber flushes (cancer is bottom bars 1, 4,7, 10; benign is bottom bars 2, 5, 8, 11; control is bottom bars 3, 6,9, 12; and water is bars at top of figure).

FIG. 5 . Sensor responses for DNA-NT based on Seql (left) show a cleardifferentiation between the plasma samples (“Cancer”, “Benign”, and“Control”), while those based on Seq4 do not (right).

FIG. 6 . Responses induced by the three serum headspace vapors forDNA-NT based on 4 different base sequences tested. Between 18 and 25sensors of each type were used (error bars are derived as explainedelsewhere herein).

FIGS. 7A and 7B. VOCs in the headspace above cell culture supernatantscollected from normal ovarian epithelial cells or OVCAR3 cells. FIG. 7Ashows most abundant compounds; FIG. 7B shows compounds at lowerconcentrations; * = p ≤ 0.001.

FIG. 8 : DNA-NT sensor discriminates VOCs emanating from supernatantscontaining metabolites of in vitro cell systems. The signal associatedwith normal ovarian cells is at the noise level (data A). The media inwhich normal ovarian cells were grown also yielded a small signal (dataB). In addition, the media in which cancerous, OVCAR3 cells were grownyields a very small signal (data C). In contrast, the supernatant from asample of cancerous ovarian cells yields a large, reproducible signal(data D).

FIGS. 9A and 9B. Analysis of Pooled Samples by GC/MS The top three plotsshow differences in selected regions in the Total Ion Chromatographsobtained from analyses of SPME-collected VOCs from the three pooledsamples (top: control group; middle: benign tumor group; bottom: ovariancancer group). The bottom two plots show the mass spectrometry data forthe two compounds that show the strongest differences. These have beenidentified as 3,4-dimethylbenzaldehyde (top mass spectrum) anddimethylsulfone (bottom mass spectrum).

FIG. 10 . Success of canine biosensing of ovarian cancer. Dogs wereexposed to 50 uL of plasma pooled from 10 ovarian cancer patients (truepositive), 10 patients with benign ovarian disease and 10 age matchedcontrols. Mean proportion of success = number of correct trials/totalnumber of trials.

FIG. 11 . “Radar plot” comparing the VOC profile of the three subjectgroups; healthy controls; ovarian cancer; and benign tumors . Thez-transformed data show significant differences among the three groups.

FIG. 12 . Visualzation of GC/MS data from individual plasma samples. Thevector representing VOCs for each subject, as determined by SPME-GC/MS,is projected along the vector connecting the average response of healthycontrols and that of patients with malignant cancer. Triangles along thex-axis correspond to each sample tested. The data points from themalignant, benign and control classes are offset vertically to avoidobscuring data. Gaussian curves are estimated distributions of eachgroup, based on the mean and standard deviation. The distributionsassociated with malignant and benign tumors are clearly distinguishedfrom that of the healthy controls, as indicated by the p-values of0.0042 and 0.0033, respectively.

FIG. 13 : Visualization of DNA-NT sensor data from individual plasmasamples. The response vector for each subject is projected along thevector connecting the average response of healthy controls and that ofpatients with malignant cancer. Triangles along the x-axis of the plotcorrespond to each sample tested. Vertical offsets of malignant, benignand control classes are to avoid obscuring data. Control data are highlyclustered and show minimal overlap with the malignant and benign sets.Gaussian curves are estimated distributions of each group, based on themean and standard deviation. malignant and benign tumors are clearlydistinguished from that of the healthy controls, as indicated by thep-values of 3 × 10⁻⁵ and 6 × 10⁻⁵, respectively.

FIGS. 14A-14C (DNA-NT Nanosensor Array). FIG. 14A provides a schematicof interdigitated electrodes for FET with channel width 10 µm and achannel length of 1 mm. FIG. 14B provides an Atomic Force Microscopeimage of the channel region of a CNT FET. A sparse network of CNTsbridges the gap between the electrodes. FIG. 14C provides a photographof a FET sensor array consisting of 100 ssDNA CNT FET devices. Theinterdigitated channel regions are on the left side of the chip, whilecontact pads extend to the left. Ten sets of 10 devices each arespatially separated for independent functionalization with a specificDNA oligomer.

FIG. 15 presents exemplary linkage chemistries that may be used to linka detection moiety to a substrate.

FIG. 16 presents an exemplary embodiment in which a single nanotubeconnects two electrodes; as shown, a detector moiety (e.g., apolynucleotide) is in electronic communication with the nanotube.

FIG. 17 presents an exemplary embodiment of an array of sensorsaccording to the present disclosure placed in a chamber where a vaporsample is flowed across the array and signals from the array arecommunicated to a computer or other device for further analysis.

DETAILED DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS

The present invention can be understood more readily by reference to thefollowing detailed description taken in connection with the accompanyingfigures and examples, which form a part of this disclosure. It is to beunderstood that this invention is not limited to the specific devices,methods, applications, conditions, or parameters described and/or shownherein, and that the terminology used herein is for the purpose ofdescribing particular embodiments by way of example only and is notintended to be limiting of the claimed invention. Also, as used in thespecification including the appended claims, the singular forms “a,”“an,” and “the” include the plural, and reference to a particularnumerical value includes at least that particular value, unless thecontext clearly dictates otherwise. The term “plurality”, as usedherein, means more than one. When a range of values is expressed,another embodiment includes from the one particular value and/or to theother particular value. Similarly, when values are expressed asapproximations, by use of the antecedent “about,” it will be understoodthat the particular value forms another embodiment. All ranges areinclusive and combinable.

It is to be appreciated that certain features of the invention whichare, for clarity, described herein in the context of separateembodiments, can also be provided in combination in a single embodiment.Conversely, various features of the invention that are, for brevity,described in the context of a single embodiment, can also be providedseparately or in any subcombination. Further, reference to values statedin ranges include each and every value within that range. Any documentscited herein are incorporated herein by reference in their entiretiesfor any and all purposes. It should also be understood that a referenceto a particular testing condition (e.g., testing on ovarian cancer) isillustrative only and does not limit the disclosed technology to thatparticular condition.

Ovarian cancer is the most lethal of the gynecological cancers and thefourth leading cause of cancer death in women. When diagnosed early,ovarian cancer has a favorable cure rate; however, more than 80% ofpatients are diagnosed at a late stage, when even aggressive treatmentis unable to effect a cure. Any advance that can lead to more accuratedetection of ovarian cancer in its early stages can have a great impacton overall survival. But despite extensive investigation, there is nosufficiently accurate screening test for early detection of ovariancancer in women of average risk. Studies suggesting that early diagnosisis possible using serum proteinaceous biomarkers appear to becontroversial and disputed.

In one embodiment, the present disclosure provides detection devices.The devices may include a semiconductor material (e.g., doped silicon,nanotubes - including carbon nanotubes, graphene, and the like) and adetection moiety in electronic communication with one another. One suchembodiment is shown in FIG. 16 . As shown in that figure, a device isconstructed with two electrodes (not labeled) atop a SiO2 substrate(which in turn is atop a Si substrate). A carbon nanotube (magnified) ispresent between the two electrodes, and a detector moiety (e.g., apolynucleotide) is in electronic communication with the nanotube.Molecules of interest interact (e.g., bind) with the detector moiety,and changes in signal related to those interactions are then collectedand further analyzed. As shown in the figure, voltage and currentsources are in electronic communication with the device.

The detection moiety may be configured (or chosen, selected, or evenmodified) to detect one or more volatile organic compounds present in abiological sample. The devices may also include a sensor chamber (e.g.,an enclosed vessel, such as a cup, tub, tube, beaker, cylinder, dish,bowl, or other such vessel). The device may be configured such that thedetection moiety is capable of fluid communication with the interior ofthe sensor chamber. As one example, the detection moiety may be disposedin the sensor chamber. Alternatively, one or both of the moiety andchamber may be capable of motion relative to the other, e.g., such thatthe moiety may be insertable into the chamber, or even such that thechamber may be moveable so as to enclose the detection moiety.

In one embodiment, the chamber is sealed against the externalenvironment in order to retain the VOCs. The detection moiety ormoieties may be located in the headspace of the sensor chamber so as toplace them into contact with the VOCs when the VOCs are present.

It should be understood that the present disclosure provides kits. Thekits may include a device that comprises a detector moiety, a substrate(in electronic communication with the detector moiety). The device mayinclude one or more connections in electronic communication with thesubstrate. The device may also include a chamber configured to contain asample from which the detection moiety may detect VOCs. The chamber mayeven be a syringe or other similar chamber into which a user mayintroduce (e.g., via puncture, via pipetting, injecting, or by othermethods) a sample. The kit may also include a heater configured to heatthe sample within the chamber to encourage release of VOCs from thefluid sample; a kit may also include a plunger, membrane, or other partthat a user may manipulate to change the pressure within the chamber.The kit may include a reader device (e.g., a display or even an LED orother indicator) that provides information regarding one or more signalsfrom the detection moiety, e.g., a signal that relates to the presenceor absence of a VOC to which the detection moiety is sensitive. The kitmay also include a power source used to provide power to the device. Inthis manner, the present disclosure provides kits that may be used as anon-site detection system for one or more VOCs that are suggestive of acondition. The kit may include instructions and other documentation soas to enable use by a variety of personnel.

A variety of materials are considered suitable semiconductors. Thesemiconductor may include, e.g., graphene, a carbon nanotube (i.e., oneor more carbon nanotubes), MoS₂, silicon, zinc oxide, WS₂, silicon,germanium, gallium arsenide, indium phosphide, gallium nitride, or anycombination thereof. Graphene is considered an especially suitablesemiconductor, as are carbon nanotubes.

The semiconductor may be tubular, planar, curved, plate-shaped, or ofvirtually any other configuration, e.g., a ribbon, a strip, a ring, aloop, a C-shape, a T-shape, an L-shape, a U-shape, or otherconfiguration. The semiconductor may be in electronic communication witha conductor, e.g., a wire, lead, pin, or other conductor (e.g., ametal). Nanotubes and nanowires are considered especially suitable.

A semiconductor substrate may have a cross-sectional dimension (e.g.,width, length height, diameter, thickness, radius, and the like) in therange of from 0.5 nm to 10 cm, from 1 nm to 5 cm, from 10 nm to 1 cm,from 100 nm to 1 mm, or even from 50 nm to 0.5 mm. A semiconductorsubstrate may be individually addressable. In some embodiments, a devicemay include one, two, three, or more substrates in electroniccommunication with one another.

Devices according to the present disclosure may include one or morevalves configured to modulate fluid communication between the detectionmoiety and the interior of the sensor chamber. The valve may be manuallyactuated or actuated in an automatic fashion, e.g., by a computercontrolled configured to open (or close) the valve in response to aparticular signal or control. Such a signal may be related to a level ofan analyte, the passage of time, the position of a component, an amountof material, or some combination thereof.

A device may include a sample chamber. The sample chamber may be capableof fluidic communication with the interior of the sensor chamber. Forexample, a biological sample may be placed in the sample chamber, andthat sample chamber may in turn be in fluid communication with thesensor chamber. It should be understood that in some embodiments, thesensor chamber is configured to contain a biological sample. In someembodiments, the detection moiety may be capable of fluid communicationwith a headspace of the sensor chamber. As described elsewhere herein,the detection moiety may be disposed within the sensor chamber. Achamber may be plastic, metal, flexible, rigid, or any combinationthereof. The chamber may be removeable or separable from the device. Thechamber may include one or more inlet ports or other entry points atwhich a sample may be introduced. A detector may also be inserted intothe chamber by way of an inlet or other entry port. The presentdisclosure should be understood as including kits, which kits mayinclude a chamber, a detection moiety, and a semiconductor. A user mayassemble together one or more of these components.

An exemplary device is shown in FIG. 17 . As shown in that figure, asensor array chip may be disposed within a chamber. A sample isintroduced to the chamber via the inlet (“Vapor in”) and then contactsthe sensor or sensors on the chip. The sample interacts with the variouscomponents of the sample which in turn generates one or more signalsthat are then communicated to a computer or other device for furtheranalysis. The chamber may include an outlet (“Vapor out”) to allow thesample to exit. It should be understood that a sample may be liquid andthen be vaporized (or partially vaporized) in the chamber so as torelease VOCs from the sample. The detector may be in the headspace ofthe chamber so as to allow the detector to contact VOCs without alsocontacting a liquid sample.

A device may include two or more detector moieties that differ from oneanother in structure. A detection moiety may include a polynucleotide, apolypeptide, a nucleic acid-polypeptide complex, a carbohydrate, anaptamer, a ribozyme, and any and all homologs, analogs, conjugates, orderivatives thereof, as well as mixtures thereof, or any combinationthereof. A detection moiety may be a protein, e.g., an olfactoryreceptor protein or a water soluble variant of an olfactory receptorprotein. Olfactory proteins and their variants are considered especiallysuitable detection moieties.

A detection moiety may be a polyonucleotide, as described. Apolynucleotide may be one or more of, for example,5' GAG TCT GTG GAG GAGGTA GTC 3' (SEQ ID NO: 1), 5' CTT CTG TCT TGA TGT TTG TCA AAC 3' (SEQ IDNO: 2), 5' CCC GTT GGT ATG GGA GTT GAG TGC 3' (SEQ ID NO: 3), 5' GTA CGGACT GTG AAT GCG CGT TAG 3' (SEQ ID NO: 4), or any combination thereof. Apolynucleotide may be randomly selected or generated but may also bepreselected. A polynucleotide may include 2, 5, 10, 20, 50, 100, 150,200, or even 1000 bases, as well as all intermediate values. Likewise, apolypeptide may include, e.g., from 2 to 50 amino acids. It should beunderstood - as explained below - that proteins and polypeptides areboth suitable detector moieties.

A detection moiety may also be a polypeptide, such as a protein or othersuch structure. A detection moiety may be a monomer or polymer;copolymers (including block copolymers, graft copolymers, and the like)are considered suitable. Receptors and ligands are also consideredsuitable detector moieties. Detector moieties that exist in connectionwith olfactory systems (e.g., olfactory proteins from mammals) areconsidered especially suitable.

Detection moieties may be configured to detect one or more pre-selectedvolatile organic compounds. Exemplary such compounds may includedimethylsulfone, 3,4-dimethyl benzaldehyde, an alkyl substitutedpyridine, cyclohexanone, 2-pentylfuran, caprolactam, or any combinationthereof. VOCs that show differences between patient groups and controls(e.g., 2-methylpyridine) are considered particularly suitable.

The disclosed devices may include a monitor, which may be in electroniccommunication with the detector moiety. The monitor may be configured todetect a signal, a change in signal, or both related to an interactionbetween the detection moiety and a volatile organic compound of abiological sample. Suitable such signals may include a current, voltage,a current-gate voltage, resistance, or any changes or combinationthereof.

Optical or visual signals may also be monitored. Such signals includeintensity, wavelength, and the like; as one example, a user mightilluminate a detection moiety with a laser or other beam so as to detectoptical signal changes related to an interaction between the detectionmoiety and a VOC. Changes in signals may include a change in current, achange in voltage, a change in resistance, a change in current-gatevoltage characteristic, a change in intensity, a change in wavelength,or any combination thereof.

A detection moiety may be covalently bound to the semiconductor, e.g.,by using an amide, thiol, peptide, histidine tag linkage, or, e.g., alinkage between nickel-nitriloacetic acid group and a histidine residue.Linkages that include a chitin binding protein, a maltose bindingprotein, glutathione-S-transferase, an epitope tage, or any combinationthereof are also suitable, as are cysteine-graphene linkages, amidebonds (e.g., between a protein and graphene), an imine bond (e.g.,between a protein and graphene), a thiourea bond (e.g., between aprotein and graphene), an aminoalcohol bond (e.g., between a protein andgraphene), and the like.

In some embodiments, a protein may be bound to graphene by a peptidesequence. In one embodiment, a protein may be attached to graphene byadding a specific peptide sequence, such as one that is identified usinga phase display peptide library. Graphene may itself be modified tocomprise a moiety to facilitate attachment. Such moieties includesugars, antibodies, a chitin binding protein, a maltose binding protein,glutathione-S-transferase (GST), an epitope tag, and the like. Suitableepitope tags include a V5-tag, a c-myc-tag, a HA-tag, or any combinationthereof. Proteins used in the disclosed devices may include a reactiveamino acid, which includes photoreactive amino acids.

The graphene of the disclosed devices may include a diimide-activatedamidation between the graphene and biomolecules. The devices may alsoinclude a cysteine-graphene linkage between the graphene andbiomolecules. Such a linkage may be effected by treatment withdiazonium, EDC NHS, PDEA aka 2-(2-pyrdinyldithio) ethaneamine, with athiol-bearing region of the protein.

A variety of linkages may be used to connect a biomolecule to graphene,including an amide bond between the biomolecules and graphene, an iminebond between the biomolecule and graphene, a thiourea bond between thebiomolecule and graphene, an aminoalcohol bond between the biomoleculeand graphene.

Ionic bonds may be used as well. A detection moiety may be bound to thesemiconductor by pi-pi orbital interaction, by hydrogen bonding, bycoordination bonds, or by other bonds known to those in the art. Stillmore exemplary linkages are shown in non-limiting FIG. 15 .

In some embodiments, the device may be configured to encourage releaseof one or more VOCs from a sample. A device may include a heaterconfigured to encourage release of one or more volatile organiccompounds present in the biological sample. A device may also include asource of reduced pressure configured to encourage release of one ormore volatile organic compounds present in the biological sample. Such asource may be a vacuum device (including automated vacuum devices aswell as a a plunger, membrane, or other part that a user can move), andthe pressure may be 99%, 90%, 50%, 10%, 5%, 1%, or even 0.5% ofatmospheric pressure. The pressure, heat, or addition of material (e.g.,salt, as described elsewhere herein) may be modulated singly or togetherso as to effect release of one or more VOCs from the biological sample.The source of reduced pressure is suitably configured to reduce thepressure exerted on the biological sample such that VOCs are released(or to speed VOC release) from the sample. Likewise, the heater issuitably configured to increase the temperature of the sample (or nearbyto the sample) such that VOCs are released (or to speed VOC release)from the sample.

A device may also include a volatile organic compound from a biologicalsample in interaction with the detection moiety. The interaction may bea chemical bond (e.g., covalent, ionic, hydrogen bonding, coordination)or some electronic interaction. As described elsewhere herein, such aninteraction suitably gives rise to a change in signal (e.g., current)related to the interaction between the VOC and the detection moiety.

It should be understood that the present devices may be configured toassess the presence of one, two, three, or more VOCs. A device may alsoinclude an array of semiconductors and detection moieties such that thedevice is configured to assess the presence (or absence) of multipleVOCs. The devices may also be configured to assess the presence (orabsence) of one, two, or multiple disease states. As one example, adevice might include a first set of detector moieties that areconfigured to detect the presences of VOC1, VOC2, and VOC3, which threeVOCs are characteristic markers for ovarian cancer. The device mayinclude a second set of detector moieties that are configured to detectthe presences of VOC4, VOC5, and VOC6, which VOCs are characteristicmarkers for lung cancer. The device may then be used to assess thestatus of a biological sample for ovarian and another cancer, e.g.,breast cancer. It should be understood that the present disclosure isnot limited to ovarian cancer, as the technology may be applied to othercancers, e.g., lung cancer, gynecologic carcinomas, and the like.

The present disclosure also provides methods. The methods may includeexposing a device according to the present disclosure to an atmosphereabove a biological sample from a patient, the atmosphere comprising oneor more volatile organic compounds of the sample; and detecting asignal, a change in signal, or both related to exposing the device tothe atmosphere.

The methods may further include adding a material to the biologicalsample that encourages one or more volatile organic compounds from thesample into the atmosphere, heating the biological sample, applying areduced pressure to the biological sample, or any combination thereof.The material may be a salt, e.g., NaCl, KCl, CaCl, or other salt. Themethods may also include heating the sample to as to encourage releaseof VOCs from the sample. The heating may be performed to raise thesample temperature by 1 deg. C, 5 deg. C, 10 deg. C, 20 deg. C, 50 deg.C, 75 deg. C, or more. A sample may be brought to boil in someembodiments.

As described elsewhere herein, suitable signals may include a current,voltage, resistance, current-gate voltage characteristic or anycombination thereof. The change in signal may include a change incurrent, a change in voltage, a change in resistance, or any combinationthereof. As described in the non-limiting examples presented herein,changes in current are considered particularly suitable.

The methods may further include correlating the signal, the change insignal, or both, to a disease state of the patient. For example, achange in a current signal may correlate to the presence of acancer-marking VOC in the atmosphere to which a device has beencontacted.

A disease state may be cancer, a gastrointestinal disorder, aninfection, or other disease. Cancer disease states include all forms ofcancer, e.g., ovarian cancer, breast cancer, lung cancer, prostatecancer, or any combination thereof.

Correlating may include, e.g., comparing the signal, change in signal,or both to a signal, a change in signal, or both to a standard. Astandard may be a well patient, a disease state patient, or othercomparator. The correlation may include differences in signal,differences in rate of change of signal, absolute rates of change ofsignal, integration (area-under-curve) of signal vs. time, and the like.

The methods may include clearing the device so as to return the deviceto a baseline. The clearing may be performed so as to return the deviceto a “clean” state from which the device may be reused. Clearing mayinclude applying a carrier fluid, e.g., ambient or breathing air,nitrogen, or argon, purified air, or some combination thereof. Clearingmay also include applying a fluid (e.g., water, an electrolyte, asolvent, and the like) that releases VOCs from the detection moieties sothat the detection moieties may be used in a later analysis. A systemmay include a routine that zeros the signal of a ‘clear’ detectionmoiety so that each analysis begins with a ‘zero’ baseline signal.

A variety of biological samples (including bodily fluids) may be used.For example, whole blood, serum, plasma, saliva, vaginal secretions,urine, mucus, phlegm, semen, cell culture media, cell culturesupernatant, or any combination thereof. Serum is consideredparticularly suitable but is not the exclusive biological samplesuitable for the disclosed technology.

Additionally provided are methods, the methods including effectingrelease of one or more volatile organic compounds from a biologicalsample into an atmosphere; contacting the atmosphere and a detectionmoiety in electronic communication with a semiconductor; and detecting asignal related to the contacting, detecting a change in signal relatedto the contacting, or both.

Suitable detection moieties and semiconductors are described elsewhereherein. Detecting a signal, a change in signal, or both, may be relatedto exposing the device to the atmosphere. The effecting may includeheating, reducing pressure, adding an agent that encourages one or morevolatile organic compounds from the sample into the atmosphere, or anycombination thereof. As described elsewhere herein, the signal, thechange in signal, or both, may be related to interaction between avolatile organic compound and the detection moiety.

The methods may further include comparing the signal related to thecontacting, the change in signal related to the contacting, or both, toa standard. The methods may also include correlating the signal, thechange in signal, or both, to a disease state, e.g., cancer or otherdisease state.

Some exemplary analyses are provided of the VOC signature of ovariancancer based on serum samples collected from ovarian cancer patients,patients with benign ovarian tumors, and age-matched, healthy controls.Measurements of pooled serum samples from these three populations showthat their respective odor profiles can be differentiated usingDNA-decorated carbon nanotube vapor sensors (DNA-NT). This finding wasconfirmed by experiments based on the analytical technique solid-phasemicroextraction gas chromatography/mass spectrometry (SPME-GC/MS) andtrained detection dogs, both of which showed discernable differencesamong samples derived from the three patient pools.

Cells release odorants that possess finite vapor pressures at bodyand/or ambient temperatures. These VOCs can be found emanating from allbody fluids. As cells turn malignant, analysis of these odorantsprovides insight into cancer diagnosis. Thus, one may screen for ovariancancer (or other conditions) through analysis of VOCs with advancednanosensors such as DNA-NT.

Specific to ovarian cancer, dogs were trained to distinguish ovariancancer tissues of various stages and grades from normal ovarian tissueand other gynecological malignancies with sensitivity and specificityover 95%; when trained on tissue, dogs were able to detect the VOCdisturbances in peripheral blood samples with the same accuracy. Resultsfrom a study (FIG. 1 ) are consistent with these earlier reports andindicate high sensitivity and selectivity for pooled samples of plasmafrom ovarian cancer patients over pooled samples from health controls(n=10 for each).

SPME-GC/MS is a sensitive method to collect, detect and identify themolecules in the VOC signature that distinguishes patients with ovariancancer from controls. One may find differences in the VOC profiles foreach category of pooled plasma samples from patients and controls (FIGS.2A and 2B). Dimethylsulfone, a common metabolite of methionine, differedamong groups with the largest amounts present in the cancer pool.Another observed difference related to an unknown compound at retentiontime ca. 21.60 minutes. The mass spectrum of this compound (FIGS. 2A and2B) suggests - without being bound to any particular theory - that it isa substituted benzaldehyde. None is detected in controls.

Single-walled carbon nanotube field effect transistors (FETs) coatedwith single stranded DNA (DNA-NT) show a change in source-drain currentupon exposure to VOCs and VOC mixtures. DNA-NT responses are controlledby the DNA base sequence. The sensor class is thus suited for an arraywith a number of sensors with uncorrelated odor responses, as requiredfor a system with computational power approaching that of mammalianolfaction.

In one exemplary experiment, arrays of 56 devices each were fabricatedin parallel on Al₂O₃ coated Si/SiO₂ wafers by first usingphotolithography/metallization to produce Cr/Au electrodes and then dropcasting semiconducting-enriched (98%) nanotube solution (NanoIntegrisInc.) onto the chips. Washing, cleaning, and annealing steps wereperformed to remove surfactants and ensure electrical contact betweenthe CNTs and gold electrodes. Finally, DNA functionalization wasperformed by pipetting a 100 µM DNA solution (Invitrogen Co.) onto thedevices and allowing the DNA strands to diffuse to and bind onto thesidewalls of the CNTs. The DNA strands bind via the π- π stackinginteraction between the DNA bases and the CNT surface; as describedelsewhere herein, other electronic interactions are also suitable.

After 30 minutes, the DNA solution was blown off the chip withcompressed nitrogen gas, removing unbound DNA, and the devices wereready to use. It should be understood that devices can be produced invarious ways and still maintain the same basic characteristics. As butone example, carbon nanotubes could be grown by chemical vapordeposition or other methods, and DNA could be applied using any one of anumber of spotting techniques.

Before the DNA functionalization and sensing experiment, the CNT deviceswere characterized electronically by conducting a three terminal currentvs. gate voltage measurement using the global silicon back gate. Asshown in FIG. 3 , the devices showed reproducible p-type electronicbehavior, with ~ 95% of the devices exhibiting on-off ratios exceeding20 and a narrow range of turn-off voltages centered around zero volts.

To compare devices with different on-state currents, the sensor responseis reported as the percentage change in the current . The gate voltagewas held fixed at -8 V for all vapor sensing measurements to maintain ahigh current level and transconductance, with the goal of maximizing thesignal-to-noise ratio

To increase the concentrations of VOCs in the headspace of the samples,125 mg of NaCl was added to a 500 µL serum sample in a 25 mL two-neckround-bottom flask which makes the serum less hospitable for VOCs anddrives them into the vapor phase. The sample was also heated to 45° C.and stirred vigorously with a miniature stir bar.

A mass flow controller (MFC) was connected to the inlet of theround-bottom and a check-valve was connected to the outlet, keeping theheadspace isolated until any carrier gas was pulsed through. The closedheadspace was left to accumulate volatiles for 30 minutes, after whichnitrogen carrier gas was passed through the MFC, pushing a stream ofVOCs from the serum sample out of the round-bottom towards the sensorchamber.

Experimental Procedure

An array of DNA-NT sensors was placed into a chamber of size 6 cm × 2.5cm × 1 cm with electrical feedthroughs to allow the conduction of eachsensor to be monitored. An inlet and outlet allowed the environment tobe controlled. The 3 different pooled serum samples (cancer patients,patients with benign tumors, healthy controls) were tested in the sameexperimental run. The flow recipe used is shown in FIG. 4 . For thefirst 30 minutes, water vapor from a bubbler was flown into the chamber.During this time, the headspace of each of the serum samples was closedoff, and the salted serum samples were heated and stirred as describedabove, allowing the VOCs to build up in the headspace. After 30 minutes,headspace vapor from the first serum sample was pulsed into the sensorchamber for two minutes, followed by 2 min of flowing clean air carriergas, which was determined to restore the sensor response to baseline.This cycle of 2 min of exposure to vapor and 2 min purging with cleanair was repeated for the other two pooled plasma samples, and the fullcycle of exposure to each of the plasma samples rate (200 sccm) and therelative humidity (100%) were constant through the entire experiment.While not necessary, one may keep the total flow rate and humidityconstant to help ensure that all sensor signals were due to the presenceof the volatiles from the serum and not a different environmentalfactor.

Vapor Sensing Results and Analysis

Data streams were collected from an array of 21 DNA/NT devices based onthe same DNA sequence, and the measurements from the devices wereaveraged to enhance the signal-to-noise characteristics. DNA-NT based onDNA of different base sequences showed different behavior, as expected,as device responses are known to depend sensitively on the DNA basesequence. Responses of DNA-NT based on Seq1 showed strongdifferentiation between the three pooled plasma samples (FIG. 5 , leftpanel). In contrast, DNA-NT based on Seq4 showed almost identicalresponses to the three samples tested.

FIG. 6 is a summary of sensor responses for the four sequences tested.One analysis would be to determine the average response across alldevices and its uncertainty for each plasma type. In some cases, anindividual device that responded more strongly than the average to oneparticular serum vapor was also likely to respond more strongly to theother serums. One may account for this by normalizing all responsemagnitudes for each device to the average response of that particulardevice to vapor from the control serum. These ratios are then averagedacross all devices based on a particular DNA sequence. Finally, theratios and their uncertainties are multiplied by the average controlserum vapor response magnitude to retain the units of ‘percent currentchange.’

The four sequences tested all show different overall responsecharacteristics to the samples tested. DNA-NT based on Seq4 are unableto differentiate among the serum samples. Devices based on Seq2differentiate between vapors from serum from patients with tumors(cancerous or benign) and serum from the healthy controls, but there isno distinction between the samples from patients with tumors. Devicesbased on both Seq 1 and Seq 5 are able to distinguish all three serumtypes. However, while devices based on Seq 1 respond more strongly tothe benign serum than the cancer serum, the opposite is true forsequence 4. Without being bound to any particular theory, this is notunexpected, given that the electrical response of DNA-NT depends on thecomplex interaction between the complex VOC mixture from the headspacevapor and the binding sites on the sensor, which depend upon the DNAbase sequence.

Thus, present here is a screening technology for ovarian cancer based onelectronic detection and differentiation of vapors from serum samples.Vapors from pooled serum from women with ovarian tumors induced aclearly different response in DNA-coated carbon nanotube sensors thanvapors from serum from healthy women. Moreover, the sensors were able todistinguish between pooled serum from women with benign tumors andpooled serum from donors with malignant tumors.

Screening analysis can be performed in minutes and the sensors are evenreusable due to the non-covalent, short-lived attachment of the volatilemolecules in the serum headspace to the sensor’s DNA coating. Sensorsare fabricated using scalable techniques that would be economicallyattractive. Further studies using serum samples from individual donorsmay be used to assess the variation between individuals that compriseeach pooled group.

Definitions of exemplary, non-limiting DNA base sequences:

Seq1 - 5' GAG TCT GTG GAG GAG GTA GTC 3' (SEQ ID NO: 1)

Seq2 - 5' CTT CTG TCT TGA TGT TTG TCA AAC 3' (SEQ ID NO: 2)

Seq4 - 5' CCC GTT GGT ATG GGA GTT GAG TGC 3' (SEQ ID NO: 3)

Seq5 - 5' GTA CGG ACT GTG AAT GCG CGT TAG 3' (SEQ ID NO: 4)

ADDITIONAL DESCRIPTION

The following is additional supporting (but non-limiting) disclosure. Aspresented elsewhere herein, presented here is, inter alia, exploitationof volatile metabolites that may serve as biomarkers of the disease.Small organic compounds that possess vapor pressures at body and/orambient temperatures give rise to odors (e.g., VOCs), and thesecompounds may be used as disease markers.

Translation of these biomarkers into functional diagnostic indicatorsthat a physician can use in a clinical setting is one object of thepresent disclosure. One may use single walled carbon nanotube fieldeffect transistors (FET’s) functionalized with single stranded DNA(ssDNACNT) or other detection moieties and examine the change in sourcedrain current when exposed to VOCs. By varying the sequence of theadsorbed ss-DNA, the response of the ssDNACNT system can be tuned fordesired sensitivity and specificity. The disclosed sensor class has aunique set of properties making them ideal for use in sensor arrays aspart of what can be termed a “nanotechnology-enabled electronic nose”(NTE-nose) system.

It should be understood that a sensor can be constructed by testingvarious nucleotide sequences against various samples to determine whichsequence or sequences yield a detectable signal when contacted with aparticular analyte. For example, a user might generate three random10-mer sequences and test those sequences against a disease sample and awell sample to see which of the sequences provides with the best way todistinguish between the two samples.

A sensor might thus contain five random 10-mer sequences, be calibratedagainst a control (well) sample, and then be calibrated against adisease sample so as to determine which of the sequences provided thegreatest difference in signal when contacted with the two differentsamples. In this way, a user may construct a “library” of sequences andcategorize the sequences by their sensitivity to particular samples.Similarly, a user might categorize sequences by their sensitivity tovarious VOCs so as to arrive at a library organized by the ability ofits members to detect certain VOCs. Likewise, a user may generate alibrary of signals related to the interactions of various VOCs withvarious detector moieties (e.g., different polynucleotides) - once thatlibrary is generated, a user may then contact a given detector moiety toa sample (with one or more unknown VOCs) so as to generate a signal thatis then compared against the signal library. The user may then determinewhich library signal most closely matches the sample signal, thusallowing the user to identify the VOC in the sample.

A user might also then compare a sequence’s sensitivity to a particularVOC to the VOCs evolved from a particular disease sample so as to arriveat a sequence or set of sequences that are particularly suited to detectVOCs evolved from a particular sample and hence to determine theunderlying condition of the patient that provided the sample from whichthose VOCs evolved.

A user may determine a “panel” that includes a set of detection moieties(e.g., three polynucleotides of different sequence) that is used toassay for the presence of one or more VOCs. In this way, a user mayassemble a sensor that includes one, two, or more panels, and in thisway a user may construct a custom device that includes panels ofdetection moieties so as to enable the device to detect the diseasestates (or VOCs) of interest to the user. Alternatively, a user mayassemble devices that are configured to detect a preselected set of oneor more VOCs known to be characteristic of specific device states.

The sensors may exhibit rapid response and recovery (on the order ofseconds, or faster), very low signal drift, and chemical responses thatare controlled by the base sequence of the ssDNA, The large number ofdistinct sequences even for short oligomers (> 10¹² for strands of 20bases) makes it possible to generate hundreds of sensors withuncorrelated odor responses as required for an e-nose with computationalpower approaching that of mammalian olfactory systems. The CNT FETfunctions as an array-able electronic readout element that is sensitiveto variations in the electrostatic environment.

ssDNA may be chosen for functionalization of the CNTs because itdisplays recognition for VOCs, and the ssDNA may, in some embodiments,bind via a non-covalent π-π stacking interaction to the CNT; thisinteraction preserves the latter’s electronic readout properties. Thesesensors are capable of differentiating not only homologous series ofcompounds (aldehydes, carboxylic acids) but also structural and opticalisomers, such as discriminating enantiomers of (±)-limonene. Althoughthese compounds are all distinguishable by the human sense of smell,discrimination at the single carbon atom level by artificial electronicbased sensors has been virtually unexplored. The present disclosureprovides compelling evidence that a system with ssDNACNT sensorsprovides a powerful and functional electronic olfactory system that canbe used to detect the presence of ovarian cancers, resulting in earlydetection and better prognoses.

Without being bound to any single theory, one might hypothesize that theendogenous volatile metabolites emanating from ovarian tissue wouldchange with the onset of cancer-related metabolism. VOCs emanating fromcancer, e.g., ovarian carcinoma, are thus a yet- untapped source ofinformation regarding its presence.

Methods

Analytical-Organic Chemistry Techniques: VOCs may be collected,separated and analyzed using SPME and Gas Chromatography/MassSpectrometry (GC/MS). SPME is a technology (Supelco Inc., Bellefonte,PA) that employs a thin fused-silica fiber coated with an adsorbent. Thematerials used for collection of all VOCs are the 2 cm, 50/30 µmDivinylbenzene/-Carboxen/polydimethylsiloxan (DVB/Carboxen/PDMS)“Stableflex” fibers (Supelco Corp.). VOCs evolving from a solid orliquid surface are exposed to the coated fiber and dissolve or absorb inthe coating.

Cell cultures have been demonstrated to contain a complex mixture ofcomponents; consequently, SPME collections generate a wide variety ofvolatile components. GC/MS provides both qualitative and quantitativestructural information of hundreds of components for a given sample.

Examination of Ovarian Cell lines. OVCAR3 cells were obtained along withtwo normal ovarian cell lines from the Ovarian Tissue Bank, Universityof British Columbia.

Cell Cultures: Each of the described cell lines were grown in duplicate.OVCAR 3 were maintained in RPMI 1640 supplemented with 10% fetal bovineserum and 100 µg/ml streptomycin, 100 units/mlpenicillin. Cells weregrown at 37° C. in a humidified atmosphere of 5% CO₂ in air. Normalovarian cells, viz., IOSE 385 and HOSE 120, were obtained from theCanadian Ovarian Tissue Bank, Vancouver, Canada. They were cultured in a1:1 combination of medium 199 (Sigma M5017) and MCDB 105 (Sigma M6395)containing 5% FBS and 50 µg/ml gentamicin in a humidified atmosphere of5% CO₂-95% air. Cells were subcultured with 0.06% trypsin (1:250)/0.01%EDTA in Mg2⁺/Ca2⁺-freeHBSS when confluent. Cells initially weremaintained in plastic “T25” plates containing 4 ml of appropriate mediumand were incubated at 37° C. in a humidified environment containing 5%CO₂. Media were changed 2 times a week and cells harvested once a week.The supernatants were taken from the culture media containing cells thathad reached high confluence (≥ 100,000 cells/ml).

VOCs Emitted by Ovarian Cell Cultures: SPME was used to collect VOCs;VOCs were then desorbed, separated and analyzed by GC/MS.

Collection of VOCs from cell culture supernatants: Each cell line wasgrown in duplicate. The supernatants (~5 ml each) were taken from theculture media containing cells that had reached high confluence (≥100,000 cells/ml) One milliliter of supernatant was used for eachanalysis and the remainder was frozen at -20° C. for future use. Inaddition to harvesting the cell-free supernatants to examine VOCsreleased into these media, comparable volumes (one ml) of the specificgrowth media used for each cell type were also obtained.

Volatile biomarkers of ovarian carcinoma are present and may be detectedin vaginal secretions. Vaginal secretions in normal, healthy women havepH’s between 4-5. Initially examined were the volatiles emitted byacidified supernatants from all cell types as well as media for cellgrowth. The VOCs from each supernatant were collected by solid-phasemicroextraction (SPME). This procedure involves adding 1ml ofsupernatant to a 4ml vial with a 7 mm × 2 mm Fisherbrand® micro stirringbar and 750 mg of NaCl. The vial was capped with a silicone/TFE septacap and was placed in a water bath equilibrated at 37° C. while beingstirred for 30 minutes. A 2 cm, 50/30 µmDivinylbenzene/Carboxen/Polydimethylsiloxane (DVB/Carboxen/PDMS)“Stableflex” SPME fiber (Supelco Inc., Bellefonte, PA) was exposed tothe supernatant headspace for 30 minutes. The fiber with extracted VOCswas then transferred to the GC/MS for desorption, separation, andanalysis. Hydrochloric acid and sodium hydroxide were used to adjust thepHs. To examine intra-sample variations, each cell type was cultured inthree separate batches and two of the batches from each cell type wereanalyzed.

Gas chromatography/mass spectrometry (GC/MS): A Thermo-Finnigan TraceGC/MS (Thermo Electron, San Jose, CA) system was used. The Trace GC/MSwas equipped with a Stabilwax column (30 M × 0.32 mm with 1.0 µ coating;Restek, Bellefonte, PA) which was used for separation and analysis ofthe desorbed volatiles. The following chromatographic protocol wasemployed for separation before MS analyses: 60° C. for 4 min, thenprogrammed at 6° C./min to 210° C. with a 20-min hold at this finaltemperature. Column flow was constant at 1.5 ml/min. The injection portwas held at 230° C. Operating parameters for the mass spectrometer wereas follows: ion source temperature, 200° C., ionizing energy at 70 eV;scanning frequency was 4/s from m/z 41 to m/z 300.

Data Analysis: Compounds found in each total ion chromatogram (TIC) areseparately normalized in the following manner: one may examine the massspectra of all peaks ~1% above baseline to eliminate components arisingfrom siloxanes, room air, fragrances, cosmetics, soaps, solvents, e.g.,traces of chloroform, column and septa, and solvents commonly employedin cosmetic room air products, e.g., 2-butoxy ethanol. The intensitiesof remaining components are normalized by dividing each of theirintensities by the sum of all intensities for remaining compounds. Thistransformation is comparable to other normalization methods used inGC/MS data analysis which generally normalize to the total intensity,e.g., by dividing extracted peak intensity values by the sum ofintensity values for the chromatogram.

38 compounds were chosen for quantitative comparison. The compoundsexamined were present in both types of cell growth media; as well asboth cell types. Cancer cells can markedly alter the production ofmedia-related VOCs through up-take and metabolism. The resulting data(normalized areas) were subjected to 6 multivariate analyses of variancewith SPSS (version 16). In some analyses, one may consider only p valuesof 0.001 or less as significantly different.

Results

VOCs Emitted by Ovarian Cell Cultures: In addition to harvesting thecell-free supernatants to examine VOCs released into these media, onemay also examine comparable volumes (1 ml) of the specific growth mediaused for each cell type. T25 containers can be sources of manyplastic-related VOCs. Consequently, media or the cell-free supernatantsare employed for the analyses. Vaginal secretions in normal, healthywomen have pH’s between 4-5. Initially examined were the volatilesemitted by acidified supernatants from all cell types as well as mediafor cell growth. SPME was used to collect VOCs, which were thendesorbed, separated and analyzed by GC/MS. Many compounds in the complexmixture of VOCs above the samples were eliminated from quantitativeanalyses because they were easily recognized contaminants. 38 compoundswere chosen for quantitative comparison. The compounds examined werepresent in both types of cell growth media; as well as both cell types.Duplicate analyses were performed on each cell line and growth media.The resulting data (normalized areas) were subjected to 6 multivariateanalyses of variance with SPSS (version 16). Again, one may consideronly p values of 0.001 or less as significantly different.

Adapting these conservative numbers, it was found that VOCs emanatingfrom the OVCAR3 cell lines are quantitatively very distant from thoseobtained from normal cell lines (F = 803; p =0.000004). In contrast, theVOCs emanating from the media for each cell type are quantitatively,similar (F = 3.39; p = 0.132).

These results are depicted in FIGS. 7 a and 7 b , which demonstrates thepreponderance of significantly higher VOCs from the OVCAR3 cells. Onlyacetic acid and isovaleric acid are present in greater relative amountsin normal cell supernatant than in cancer cell supernatant. Acetic acidwas present in greater relative amounts in the normal cell media.However, the remaining differences are not due to differences in themedia used to grow the cells; they are the result of the differences incellular metabolic processes.

Power Analyses: Concomitant with the mutivariate analysis of variance,also examined were the power estimates for each compound analyzed. Asdescribed above, a large numbers of compounds clearly distinguishdisease from normal in these cell systems. The power estimates for thesecompounds range from 0.984 to 1.000. Increasing samples size maystrengthen the discrimination between disease and normal.

Reproducibility of analyses: Also examined was the test-retestreliability of our analytical methods during examination of ovariancells and found the reliability to be excellent. Reliability, i.e.,reproducibility, for the majority of all normalized peak areas were >0.90.

Response of single stranded DNA coated nanotubes (ssDNACNT) toSupernatants from Ovarian Cell Cultures: Employed was a single ssDNACNTvapor sensor to examine and discriminate the VOCs emanating from the invitro ovarian cell systems. Employed was ssDNA “sequence 2-alpha”(aaaacccccggggttttttttttt (SEQ ID NO: 5)) to examine the supernatantscontaining metabolites from normal ovarian cells, OVCAR3 cancer cellsand the growth media used for each. FIG. 8 demonstrates that the sensorcan clearly discriminate cancer cell emanations from normal cells andthe media used to grow cells. The test-retest reliability of thessDNACNT sensor measurements was also determined with two, one mlaliquots of the same supernatants and found to be excellent with a 0.97correlation between duplicate analyses.

The data reveal marked differences between normal ovarian cells andcommonly encountered types of cancer cells. In addition, one may alsonote that OVCAR3 and normal ovarian cells appear to metabolize leucineand isoleucine differently, which is suggested by the different relativeamounts of isovaleric acid and 2-methylbutyric acid, respectively.Cancer cells produce much greater relative amounts of the 2-methyl acidthan normal ovarian cells. Further many of the VOC differentiatingcancer from normal are acidic compounds, which may be easily identifiedand quantified in human vaginal secretions. These acids may beidentifiable in vaginal secretions which will allow one to inferabnormal changes deeper in the reproductive tract.

Additional Illustrative Results The Odorant Signature of Ovarian Cancerin Pooled Plasma Samples was Confirmed Using Three Approaches: DNA-NTSensor Arrays, Analytical Chemistry, and Trained Detection Dogs.

The odorant signature of ovarian cancer and the VOCs that constitutethis signature were examined using plasma samples collected from ovariancancer patients, patients with benign ovarian growths, and age-matched,healthy controls. Initial measurements were conducted on pooled samples(n = 10 for each class of subjects). Analyzing pools allowed observationof what may be average amounts of VOCs in each category of patients andcontrols as well as obvious differences attributed to subject status.Measurements of pooled plasma samples from the three populationsprovided strong evidence that their odorant profiles can bedifferentiated using the three complementary techniques.

DNA-NT sensor measurements were based on arrays consisting of 10different device types with 10 realizations each, for a total of 100DNA-NT sensors. Sensor response was reported as average percent changein the current across the set of identically prepared DNA-NT, since itis shown that this compensates effectively for sample-to-sampleresistance variations.

As set forth elsewhere herein, experiments were first conducted withDNA-NT sensors based on four different random oligomers that showedperformance in earlier experiments:

Seq1 - 5' GAG TCT GTG GAG GAG GTA GTC 3' (SEQ ID NO: 1)

Seq2 - 5' CTT CTG TCT TGA TGT TTG TCA AAC 3' (SEQ ID NO: 2)

Seq4 - 5' CCC GTT GGT ATG GGA GTT GAG TGC 3' (SEQ ID NO: 3)

Seq5 - 5' GTA CGG ACT GTG AAT GCG CGT TAG 3' (SEQ ID NO: 4).

DNA-NT sensors based on Seq1 showed clear differential responses to theheadspace vapor from the various pooled samples (FIGS. 5 and 6 ). Asseen in the summary plots of FIG. 6 , the other sequences led to DNA-NTsensors that showed a differential response to the control pool (Seq2),the benign tumor pool (Seq5), and no observed discrimination power(Seq4). This diverse set of responses is further evidence that thedisclosed systems function as electronic olfaction systems for detectingan odor signature of various cancers, e.g., ovarian cancer.

SPME-GC/MS is a sensitive analytical method to collect, separate andidentify the VOC signature and its individual components thatdistinguish patients with ovarian cancer from controls. It was foundthat pooled plasma samples from the three subject groups arequalitatively similar in their major components but also differquantitatively in VOC profiles.

As one example, FIG. 9 shows that dimethylsulfone, a commonly occurringmammalian metabolite of methionine, differs among groups, with thelargest amounts of the metanolite being present in the controls (topTotal Ion Chromatograph or TIC) and cancer patients (bottom TIC). Thelarge component eluting prior to dimethylsulfone is butylatedhydroxytolune (commonly referred to as BHT). BHT is an exogenouscompound that may be found in analysis of the vacutainer tubes used forblood collection.

Another possible difference in the three groups appears to be3,4-dimethylbenzaldehyde, which elutes at a retention time of approx.21.60 minutes. Without being bound to any particular theory, an initialexamination of the relative amounts of the 3,4-dimethybenzaldehyde inthe pooled samples suggests that the compound is present in highestamounts in samples from people with benign growths, less in those withovarian cancer and almost none in healthy controls.

Results from an exemplary cohort of trained canines are consistent withearlier reports on dogs trained to detect cancer in ovarian tissue aswell as blood samples. Experiments indicate the presence of an odorsignature in blood plasma, with a > 90 % success rate (# of correcttrials/total number of trials) for canine detection of pooled plasmasamples from ovarian cancer patients over pooled samples from healthycontrols (n=10 for each). In addition, dogs moved onto discriminatingplasma samples from both patient groups and healthy controls: all threedogs are at 90% or better mean proportion of success (FIG. 10 ). Oncetrained to recognize the ovarian cancer odors, the dogs are able toanalyze the signals and ignore confounding outside stimuli; dogs maythus be used (e.g., trained) to validate candidate molecules for VOCsensors.

Using Three Approaches to Detect the Odor Signature of Ovarian Cancer isDetected in Plasma Samples From Individual Patients.

Measurements of individual samples from which the pooled samples weremade, were also conducted to determine the pattern of VOCs across thethree groups of samples. The results of the canine study were presentedabove and also in FIG. 10 . GC/MS data were manually culled to eliminateexogenous compounds, and 24 compounds whose structures suggested theirorigin as human metabolites were examined across all patients andcontrols.

The relative amounts of these 24 compounds were calculated in allsamples. To better visualize the relationships across groups,z-transformed values corresponding to the relative amounts of the 24VOCs were used to create a “radar plot” (FIG. 11 ). Z-transforms withincompounds were chosen so the data could be plotted on the same axis.This figure clearly shows that with the exception of only four VOCs,normal controls produce higher relative amounts of the VOCs than eitherprimary cancer patients or those with benign, non-cancerous growths.

A second analysis methodology was developed. The method was designed tobe robust for small sample sizes, which is not the case for manystatistical techniques commonly applied to large-dimensional samples(e.g. Linear Discriminant Analysis). The SPME GC/MS output for eachindividual is a vector in a 24-dimensional space, with one dimension foreach VOC.

To account for samples that were excessively concentrated or too weak(no internal standards were used) one may normalize the size of theresponses using a “L₁ normalization”⁵ and then calculate the24-dimensional vector in “VOC space” corresponding to the averagerelative amounts of each VOC for each patient class. One may define wthe (vector) difference between the average vectors of the malignant andcontrol groups, which corresponds to the “direction” in VOC space thatbest separates the patients with malignant tumors from controls. One maythen take the projection of each individual vector along and visualizethe results by plotting along the number line (FIG. 12 ) where thex-axis represents position along the direction w For clarity, the datapoints from the three sets are offset vertically.

While there is overlap between the control and malignant data points,the distributions look clearly different. In addition, one may estimateGaussian fits to the data, based on their mean and standard deviation.

The data format is appropriate for a single Welch’s t-test to comparetwo data sets and evaluate the probability of the null hypothesis thatthe mean values for the sets are equal. With no assumptions as to thevariances of the control and malignant data, one finds p = 0.0042 forthese two data sets. Similarly, the benign and control data aresignificantly different distributions, with p = 0.0033. One may notethat a p value less than 0.01 is typically taken as strong evidence thatthe mean values for the sets are distinct.

Individual samples were also analyzed using 142 DNA-NT sensors based on10 different DNA oligomers (oligomer sequences known, but not listed soas to save space). The data show individual variation within each group,and the data agree qualitatively with results from pooled samples (FIGS.5, 6 ). Using the statistical method described in the precedingparagraph for GC/MS data, the DNA-NT sensor response data were analyzedin the 10-dimensional “sensor space” and projected onto the w direction(FIG. 13 ). The data format is again appropriate for a single tailWelch’s t-test to evaluate the probability of the null hypothesis (equalmean values for the sets). The analysis indicates that combining theinformation from responses across the full set of ten sensor typessignificantly enhances the power of the approach. The p-values for theprojections onto the difference vector were ~ 6 × 10⁻⁵ for thecontrol-malignant pair, 3 × 10⁻⁵ for control-benign, and 0.02 forbenign-malignant. This result is achieved using 10 randomly selected DNAsequences with no screening for effectiveness. This further demonstratesthat the disclosed sensors are a powerful diagnostic. In some, Thesedata demonstrate that the signature of ovarian cancer is detected inplasma samples from individual patients using each of the threeapproaches.

Additional device information is provided in FIG. 14 , which figureprovides information about an exemplary device. A set of exemplary CNTFET arrays was based on high purity (98%) semiconducting CNTs, depositedfrom a suspended solution (NanoIntegris Inc.). The substrate consistedof Si/SiO₂ wafers onto which a 20 nm thick layer of aluminum oxide(Al₂O₃) was deposited via atomic layer deposition (ALD) to promoteCNT-surface adhesion. Cr/Au electrodes were defined using standardphotolithography techniques and a sparse network of CNTs was depositedfrom solution by drop-casting onto the electrode arrays.

The electrode design used individual source fingers, interdigitated witha common drain electrode (FIG. 14A). The effective device area of 10 µm× 2 mm ensured that, even for a sparse network, many CNTs spanned eachelectrode pair, leading to a suitable device yield (e.g., over 90%) andalso good reproducibility of device properties (FIG. 14B). Additionally,the drain electrodes were sufficiently separated such that no undesiredshorting paths were created. Each FET array contained 100 devices,arranged as ten sets of ten devices. Each set may be addressedindependently for functionalization with a specific DNA oligomer, andeach device has its own contact pads such that all 100 device responsescan be recorded individually (FIG. 14B).

CNTs were then functionalized with single stranded DNA (ssDNA) sequencesranging from 21 to 24 base pairs in length by pipetting microliterdroplets of 100µM DNA solution onto the devices and allowing the DNAstrands to diffuse to and bind onto the sidewalls of the CNTs. After 30minutes, compressed nitrogen was used to remove the solution and unboundDNA strands, leaving a monolayer coating of ssDNA strands non-covalentlybound to the carbon nanotubes via π - π stacking.

What is claimed:
 1. A method, comprising: effecting release of one ormore volatile organic compounds from a biological sample into anatmosphere; contacting the atmosphere and a detection moiety inelectronic communication with a semiconductor; and detecting a signalrelated to the contacting, detecting a change in signal related to thecontacting, or both.
 2. The method of claim 1, wherein detecting asignal, a change in signal, or both is related to exposing the device tothe atmosphere.
 3. The method of claim 1, wherein the effectingcomprises heating, reducing pressure, adding an agent that encouragesone or more volatile organic compounds from the sample into theatmosphere, or any combination thereof.
 4. The method of claim 1,wherein the signal, the change in signal, or both, is related tointeraction between a volatile organic compound and the detectionmoiety.
 5. The method of claim 1, further comprising comparing thesignal related to the contacting, the change in signal related to thecontacting, or both, to a standard.
 6. The method of claim 5, furthercomprising correlating the signal, the change in signal, or both, to adisease state.
 7. The method of claim 6, wherein the disease state isselected from the group consisting of: a gastrointestinal disorder, andan infection.
 8. The method of claim 6, wherein the disease statecomprises cancer.
 9. The method of claim 8, wherein said cancer isselected from the group consisting of: ovarian cancer, breast cancer,lung cancer, and prostate cancer.